Combining PCA and nonlinear fitting of peak models to re-evaluate C 1s XPS spectrum of cellulose

Fernandez, Vincent; Morgan, David; Bargiela, Pascal; Fairley, Neal; Baltrusaitis, Jonas

doi:10.1016/j.apsusc.2022.156182

Combining PCA and nonlinear fitting of peak models to re-evaluate C 1s XPS spectrum of cellulose

Journal Article · Fri Dec 23 00:00:00 EST 2022 · Applied Surface Science

DOI:https://doi.org/10.1016/j.apsusc.2022.156182· OSTI ID:2420231

Fernandez, Vincent ^[1]; Morgan, David ^[2]; Bargiela, Pascal ^[3]; Fairley, Neal ^[4]; Baltrusaitis, Jonas ^[5]

Centre National de la Recherche Scientifique (CNRS) (France); Nantes Univ. (France); OSTI
Cardiff Univ. (United Kingdom); Engineering & Physical Sciences Research Council (EPSRC) (United Kingdom)
Institute for Research on Catalysis and the Environment of Lyon (IRCELYON) (France)
Casa Software Ltd. (United Kingdom)
Lehigh Univ., Bethlehem, PA (United States)

Cellulose is an example of a material that responds to XPS by the creation of new chemistry not present in the as-received sample. While improvements in instrumentation may be seen in general as beneficial to surface science, recent studies have shown that the consequences for some materials are detrimental. Here, in this work, these problems are illustrated through an analysis of cellulose spectra obtained during a degradation study. C 1s spectra are decomposed into two well-formed component curves that are open to chemical interpretation. In particular, a component-curve representative of pure cellulose is obtained as well as a second component curve that implies cellulose is degraded through the creation of carbon chemistry involving C—O, C$$=$$O and O—C$$=$$O. Since cellulose is a crystalline material, formed through the alignment of molecules under the influence of hydrogen bonds, the analysis and findings presented in this paper are relevant to any material analyzed by XPS whose properties are dependent on hydrogen bonds. The analysis techniques are based on an informed vectorial approach, which extracts directly from data spectral shapes that are used to monitor sample degradation via linear least squares optimization. Related mathematics of Principal Component Analysis and linear analysis are presented.

View Accepted Manuscript (DOE)

Research Organization:: Georgia Institute of Technology, Atlanta, GA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: SC0012577

OSTI ID:: 2420231

Alternate ID(s):: OSTI ID: 1908854

Journal Information:: Applied Surface Science, Journal Name: Applied Surface Science Vol. 614; ISSN 0169-4332

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (14)

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36 MATERIALS SCIENCE
Cellulose
PCA
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Combining PCA and nonlinear fitting of peak models to re-evaluate C 1s XPS spectrum of cellulose

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